The present invention relates generally to the field of facial recognition, and more particularly to improving a facial recognition system using biometric pre-filters.
Facial recognition systems are computer applications used for identifying an unknown person, or verifying the identity of a known person for access control. Facial recognition systems may be used at law enforcement agencies to identify suspects, at border crossings and airports to verify individuals against their passports, at airports to identify wanted individuals, and at casinos to catch blacklisted card counters. Tablets and laptop computers also use face recognition to allow the owner to login by face instead of typing a password. Many of the current digital cameras have a form of face detection which tells the camera what to focus on, and when to take the picture based on smile detection.
While fingerprints have been used by law enforcement for identifying suspects for many years, facial recognition systems offer automated help in identifying potential suspects even when the suspect person is uncooperative. Getting fingerprints from an uncooperative person is a lot harder than snapping a photo of them. While facial recognition may be a slow process, if the detective doesn't have a fingerprint or DNA to help with identification, then facial recognition is the next best thing. Facial recognition systems are useful in law enforcement investigations where a detective might have a picture of a suspect, and needs to determine the identity of the person in the picture.
After inputting a probe image into a facial recognition system, the first step is detecting the face apart from the background, or face localization. The next step is to extract the facial features in the photo to be employed by the facial recognition algorithm. Recognition algorithms can be divided into two main approaches, geometric or photometric. Geometric algorithms look at distinguishing facial features in feature analysis. Such facial recognition algorithms identify faces by extracting features from an image of a subject's face. Photometric algorithms, such as principal component analysis, use a statistical approach by distilling an image into values and comparing the values with templates to eliminate variances. Photometric algorithms normalize a gallery of face images, compress the data, and save only the data in the image used for facial recognition.